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A stochastic model for the generalised cell formation problem considering machine reliability

INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2011年第12期24卷 1095-1102页

作者： Arkat, Jamal Naseri, Foruzan Ahmadizar, Fardin Univ Kurdistan Dept Ind Engn Sanandaj Iran

Cell formation (CF) is the most well-known problem in designing cellular manufacturing systems. In the generalised version of the CF problem, each part has a number of alternative process plans. Two issues should be addressed in the generalised cell formation (GCF) problem: selecting the best process plan for each part and assigning machines to the cells. In addition to the minimisation of movement costs, the selection of the most reliable process plans is an important task for the GCF problem. Although the expected value (EV) method is a straightforward procedure to model stochastic situations, this method has some serious drawbacks. Therefore, we use chance-constrained programming (CCP) to model this problem. To demonstrate the advantages of the proposed model, the model is compared with the traditional GCF model and the EV model through some numerical examples. The results reveal that the proposed model is superior to the other alternatives.

关键词： cellular manufacturing systems cell formation machine reliability chance-constrained programming

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Possibilistic Stochastic Water Management Model for Agricultural Nonpoint Source Pollution

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2011年第1期137卷 101-112页

作者： Zhang, Xiaodong Huang, Guo H. Nie, Xianghui Univ Regina Fac Engn & Appl Sci Regina SK S4S 0A2 Canada

Agricultural activities are the main contributors of nonpoint source water pollution within agricultural systems. In this study, a possibilistic stochastic water management (PSWM) model is developed and applied to a case study of water quality management within an agricultural system in China. This study is a first application of hybrid possibilistic chance-constrained programming approach to nonpoint source water quality management problems within an agricultural system. Hybrid uncertainties with the synergy of fuzzy and stochastic implications are effectively characterized by the PSWM model with the following advantages: (1) it improves upon the existing possibilistic and chance-constrained programming methods through direct incorporation of fuzziness and randomness within a general optimization framework;(2) it will not lead to more complicated intermediate models and thus have lower computational requirements;(3) its solutions offer flexibility in interpreting the results and reflect the interactional effects of uncertain parameters on system conditions variations;and (4) it can help examine the risk of violating system constraints and the associated consequences. The results of the case study show useful information for feasible decision schemes of agricultural activities, including the trade-offs between economic and environmental considerations. Moreover, a strong desire to acquire high agricultural income will run into the risk of potentially violating the related water quality standards, while willingness to accept low agricultural income will increase the risk of potential system failure (violating system constraints). The results suggest that the developed approach is also applicable to many practical problems where hybrid uncertainties exist.

关键词： Water quality Nonpoint source pollution Possibilistic programming chance-constrained programming Agricultural system Uncertainty Decision making

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Optimal expansion of a coastal wastewater treatment and ocean outfall system under uncertainty (II): optimisation analysis

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Civil Engineering and Environmental Systems 2011年第1期28卷 39-59页

作者： Yeh, Shin-Cheng Chang, Chin-Hsien Chang, Ni-Bin Department of Civil and Environmental Engineering University of Central Florida Orlando FL USA

This paper presents an integrated simulation-optimisation assessment of the various physical, chemical, and microbiological processes that determine the transport and fate of key constitutes associated with coastal wastewater treatment and disposal effluents in coastal environments. The well-calibrated and validated ocean mixing simulation model - Cornell mixing zone expert system (CORMIX) - was employed in the first stage as an indispensable tool to simulate the initial dilution factor with respect to two major water quality indicators, biochemical oxygen demand (BOD) and Escherichia coli. The CORMIX outputs, which were obtained in a companion study, were used as the inputs in both deterministic and chance-constraint based stochastic programming models to evaluate a few alternatives for system planning and design. Such integration allowed the identification of the optimal expansion strategies for a large-scale coastal wastewater treatment and ocean outfall system in the city of Kaohsiung, South Taiwan. Research findings clearly indicate that the original alternative proposed by the city government, which had planned on upgrading the wastewater treatment process directly from the primary to the secondary level, is economically undesirable. Given the technology options of primary or enhanced primary treatment, in the most cost-effective expansion strategy, the optimal length of a newly constructed second ocean outfall pipe is no less than 1260m in order to gain sufficient assimilative capacity in the ocean environment. With this strategy, the BOD standards in the ocean environment are met for both Classes B and A types of ocean waters. The reliability of this system design may be assessed by taking the stochastic characteristics of sewerage inflow and diffusion and dispersion processes into consideration. Such an optimisation analysis could eventually lead to considerable cost savings of up to 75% when compared to the original, officially favoured alternative.

关键词： coastal wastewater treatment ocean outfall optimisation chance-constrained programming CORMIX systems analysis

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Long-term Scheduling of Cascaded Hydro Energy System with Distributed Water Usage Allocation Constraints

Long-term Scheduling of Cascaded Hydro Energy System with Di...

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IEEE Power and Energy Society General Meeting

作者： Bo Tong Xiaohong Guan Qiaozhu Zhai Feng Gao Systems Engineering Institute SKLMS Lab MOE KLINNS Lab of Xi'an Jiaotong University

ISBN: (纸本)9781457710001

In a hydro energy and water resource system it is desirable to optimize hydropower production with considerations of flood control, residential, agricultural and industrial water supply, navigation, environmental and ecological requirements, etc.. Incorporating complicated constraints of cascaded reservoirs and government regulation on water resource usage allocation, this paper presents a long-term scheduling problem of hydro energy and water resource system based on chance-constrained programming with uncertainties of natural water inflows and water demands of different regions. The water usage regulation with uncertain natural inflow is modeled as probabilistic chance constraints. The nonlinear and noconvex hydro plant production function is converted into mixed integer formulation and a general mixed integer linear programming (MILP) method is applied to solve this complicated scheduling problem. Preliminary numerical testing results for a river basin with cascaded reservoirs show that based on the problem formulation presented in the paper, the long-term scheduling is solved efficiently and accurately. Numerical testing for a more complex hydro system is being conducted.

关键词： Cascaded hydro energy system chance-constrained programming Long-term scheduling Mixed integer linear programming Mixed integer linear programming hydrodynamic power Water Resources cascades Water utilization Problem Formulation watersheds River basins Government Regulation

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Stochastic Optimization of Empty Container Repositioning of Sea Carriage

Stochastic Optimization of Empty Container Repositioning of ...

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The 2011 International Conference on Mechanical Properties of Materials and Information Technology (ICMPMIT 2011)

作者： Bin Wang Tao Yang School of Economics and Management Shanghai Second Polytechnic University

To improve the efficiency of empty container repositioning for a shipping company,a stochastic optimization model of empty container repositioning of sea carriage was established by chance-constrained *** objective function was to minimize the cost of empty container repositioning including shipping,rening and shortage *** the model,shipping cost was decided by the number of ship used for empty container *** constraints of the model included meeting the need of empty containers,limit to the number of empty containers provided and the capacity of *** numbers of empty containers required are *** stochastis model was transferred to an integer programming ***9.0 was used to solve the model and simulation was done under varied parameters to get a good shipping *** results show that the model can provide an effective program of empty container repositioning for a shipping company and it is a good way to raise shipping efficiency.

关键词： Container empty container line chance-constrained programming simulation

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A two-stage programming approach for water resources management under randomness and fuzziness

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ENVIRONMENTAL MODELLING & SOFTWARE 2010年第12期25卷 1573-1581页

作者： Guo, P. Huang, G. H. Zhu, H. Wang, X. L. Univ Regina Environm Syst Engn Program Regina SK S4S 0A2 Canada China Agr Univ Coll Water Conservancy & Civil Engn Beijing 100083 Peoples R China Tianjin Univ Sch Civil Engn Tianjin 300072 Peoples R China N China Elect Power Univ Beijing 102206 Peoples R China

In this study, a fuzzy stochastic two-stage programming (FSTP) approach is developed for water resources management under uncertainty. The concept of fuzzy random variable expressed as parameters' uncertainties with both stochastic and fuzzy characteristics was used in the method. FSTP has advantages in uncertainty reflection and policy analysis. FSTP integrates the fuzzy robust programming, chance-constrained programming and two-stage stochastic programming (TSP) within a general optimization framework. FSTP can incorporate pre-regulated water resources management policies directly into its optimization process. Thus, various policy scenarios with different economic penalties (when the promised amounts are not delivered) can be analyzed. FSTP is applied to a water resources management system with three users. The results indicate that reasonable solutions were generated, thus a number of decision alternatives can be generated under different levels of stream flows, a-cut levels and different levels of constraint-violation probability. The developed FSTP was also compared with TSP to exhibit its advantages in dealing with multiple forms of uncertainties. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： chance-constrained programming Decision making Fuzzy random variable Fuzzy robust programming Two-stage programming Uncertainty Water resources

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ICQSWM: An inexact chance-constrained quadratic solid waste management model

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RESOURCES CONSERVATION AND RECYCLING 2010年第10期54卷 641-657页

作者： Sun, Y. Huang, G. H. Li, Y. P. Univ Regina Fac Engn Regina SK S4S 0A2 Canada N China Elect Power Univ Sino Canada Ctr Energy & Environm Res Beijing 102206 Peoples R China Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China

An inexact chance-constrained quadratic solid waste management (ICQSWM) model is developed for planning municipal solid waste (MSW) management systems. The ICQSWM improves upon existing methods of inexact two-stage chance-constrained linear programming (ITCLP) and interval quadratic programming (IQP). It can tackle uncertainties presented as both probability distributions and discrete intervals;moreover, it can be used for analyzing various policy scenarios which are associated with different levels of economic penalties when the promised targets are violated. It can also reflect the effects of economies of scale under uncertainty. The developed method is applied to a case study of waste-flow-allocation planning within a MSW management system. The results indicate that the ICQSWM model not only provides an effective tool for reflecting system cost variations but also generates decision alternatives;the solutions obtained can thus help managers to identify desired policies under various environmental and system-reliability constraints and economic objectives. (C) 2009 Elsevier B.V. All rights reserved.

关键词： chance-constrained programming Quadratic Inexact Environment Optimization Solid waste management Uncertainty

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Quasi-linear programming Model of Stochastic Transportation Problems

Quasi-linear Programming Model of Stochastic Transportation ...

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6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM)

作者： Li, Fachao Wang, Li Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050000 Peoples R China

ISBN: (纸本)9781424437092

Stochastic transportation problems attract much attention in many fields, such as resource allocation, production management, etc. In this paper, after analyzing how to process random constraints in chance constrained programming, propose a quasi-linear pattern based on expectation and variance, moreover, give the quasi-linear programming model of stochastic transportation problems with good operability, finally, the performance of this model is discussed through an example. All these indicate the quasi-linear programming model can solve the stochastic transportation problems briefly and effectively, so it enriches methods of stochastic transportation problems.

关键词： Stochastic transportation problems chance-constrained programming quasi-linear programming model reliability coefficient

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Stochastic optimal reactive power dispatch: Formulation and solution method

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2010年第6期32卷 615-621页

作者： Hu, Zechun Wang, Xifan Taylor, Gareth Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Xi An Jiao Tong Univ Dept Elect Engn Xian 710049 Shaanxi Peoples R China Brunel Univ Brunel Inst Power Syst Uxbridge UB8 3PH Middx England

Classical optimal reactive power dispatch (ORPD) is usually formulated as a deterministic optimization problem, such that the network structure and load power injections are known and fixed. Hence, the influences of load uncertainties and branch outages are not typically considered. This paper proposes a chance-constrained programming formulation for ORPD that considers uncertain nodal power injections and random branch outages. A solution method combining both probabilistic load flow and a genetic algorithm is proposed and demonstrated in order to solve the problem. Simulations on several test systems show that the proposed method can prevent under-compensation or over-compensation of reactive power and increase voltage security margins. These advantages are achieved with the acceptable expense of a small increase in active power loss when compared with the results of classical deterministic ORPD. Several techniques are presented in order to improve the efficiency of the proposed method and case studies demonstrate the effectiveness of the techniques. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： chance-constrained programming Genetic algorithm Optimal reactive power dispatch Probabilistic load flow

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Solving chance-constrained combinatorial problems to optimality

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2010年第3期45卷 607-638页

作者： Klopfenstein, Olivier France Telecom R&D F-92130 Issy Les Moulineaux France Univ Technol Compiegne CNRS UMR 6599 Lab Heudiasyc F-60205 Compiegne France

The aim of this paper is to provide new efficient methods for solving general chance-constrained integer linear programs to optimality. Valid linear inequalities are given for these problems. They are proved to characterize properly the set of solutions. They are based on a specific scenario, whose definition impacts strongly on the quality of the linear relaxation built. A branch-and-cut algorithm is described to solve chance-constrained combinatorial problems to optimality. Numerical tests validate the theoretical analysis and illustrate the practical efficiency of the proposed approach.

关键词： chance-constrained programming Integer linear programming

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